Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference Tasks
Representing statistical information in terms of natural frequencies rather than probabilities improves performance in Bayesian inference tasks. This beneficial effect of natural frequencies has been demonstrated in a variety of applied domains such as medicine, law, and education. Yet all the resea...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2015-10-01
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| Series: | Frontiers in Psychology |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fpsyg.2015.01473/full |
| _version_ | 1811256201692839936 |
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| author | Ulrich eHoffrage Stefan eKrauss Laura Felicia Martignon Gerd eGigerenzer |
| author_facet | Ulrich eHoffrage Stefan eKrauss Laura Felicia Martignon Gerd eGigerenzer |
| author_sort | Ulrich eHoffrage |
| collection | DOAJ |
| description | Representing statistical information in terms of natural frequencies rather than probabilities improves performance in Bayesian inference tasks. This beneficial effect of natural frequencies has been demonstrated in a variety of applied domains such as medicine, law, and education. Yet all the research and applications so far have been limited to situations where one dichotomous cue is used to infer which of two hypotheses is true. Real-life applications, however, often involve situations (e.g., medical tests) where cues have more than one value, where more than two hypotheses are considered, or where more than one cue is available. In Study 1, we show that natural frequencies, compared to information stated in terms of probabilities, consistently increase the proportion of Bayesian inferences made by medical students in four conditions—three cue values, three hypotheses, two cues, or three cues—by an average of 37 percentage points. In Study 2, we show that teaching natural frequencies for simple tasks with one dichotomous cue and two hypotheses leads to a transfer of learning to complex tasks with three cue values and two cues, with a proportion of 40% and 81% correct inferences, respectively. Thus, natural frequencies facilitate Bayesian reasoning in a much broader class of situations than previously thought. |
| first_indexed | 2024-04-12T17:36:33Z |
| format | Article |
| id | doaj.art-4cf79ca6b95d412ca9d1b969fd546387 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-04-12T17:36:33Z |
| publishDate | 2015-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-4cf79ca6b95d412ca9d1b969fd5463872022-12-22T03:22:56ZengFrontiers Media S.A.Frontiers in Psychology1664-10782015-10-01610.3389/fpsyg.2015.01473153266Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference TasksUlrich eHoffrage0Stefan eKrauss1Laura Felicia Martignon2Gerd eGigerenzer3Faculty of Business and Economics (HEC Lausanne), University of LausanneUniversity of RegensburgPädagogische Hochschule LudwigsburgMax Planck Institute for Human Development, Berlin, GermanyRepresenting statistical information in terms of natural frequencies rather than probabilities improves performance in Bayesian inference tasks. This beneficial effect of natural frequencies has been demonstrated in a variety of applied domains such as medicine, law, and education. Yet all the research and applications so far have been limited to situations where one dichotomous cue is used to infer which of two hypotheses is true. Real-life applications, however, often involve situations (e.g., medical tests) where cues have more than one value, where more than two hypotheses are considered, or where more than one cue is available. In Study 1, we show that natural frequencies, compared to information stated in terms of probabilities, consistently increase the proportion of Bayesian inferences made by medical students in four conditions—three cue values, three hypotheses, two cues, or three cues—by an average of 37 percentage points. In Study 2, we show that teaching natural frequencies for simple tasks with one dichotomous cue and two hypotheses leads to a transfer of learning to complex tasks with three cue values and two cues, with a proportion of 40% and 81% correct inferences, respectively. Thus, natural frequencies facilitate Bayesian reasoning in a much broader class of situations than previously thought.http://journal.frontiersin.org/Journal/10.3389/fpsyg.2015.01473/fullvisualizationinstructionBayesian inferencetask complexitynatural frequenciesRepresentation of information |
| spellingShingle | Ulrich eHoffrage Stefan eKrauss Laura Felicia Martignon Gerd eGigerenzer Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference Tasks Frontiers in Psychology visualization instruction Bayesian inference task complexity natural frequencies Representation of information |
| title | Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference Tasks |
| title_full | Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference Tasks |
| title_fullStr | Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference Tasks |
| title_full_unstemmed | Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference Tasks |
| title_short | Natural Frequencies Improve Bayesian Reasoning in Simple and Complex Inference Tasks |
| title_sort | natural frequencies improve bayesian reasoning in simple and complex inference tasks |
| topic | visualization instruction Bayesian inference task complexity natural frequencies Representation of information |
| url | http://journal.frontiersin.org/Journal/10.3389/fpsyg.2015.01473/full |
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